Which statement about Type I errors in hypothesis testing is true?

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Multiple Choice

Which statement about Type I errors in hypothesis testing is true?

Explanation:
Type I error is the false-positive mistake in hypothesis testing: you conclude there is an effect when none exists. This happens when the null hypothesis is rejected even though it is true. That’s why this statement is the best description. We control how often this occurs with the significance level (alpha), such as 0.05. So, rejecting a true null is the classic Type I error. In contrast, not rejecting a true null is the correct decision, and not rejecting the null when the alternative is true is a Type II error.

Type I error is the false-positive mistake in hypothesis testing: you conclude there is an effect when none exists. This happens when the null hypothesis is rejected even though it is true. That’s why this statement is the best description. We control how often this occurs with the significance level (alpha), such as 0.05. So, rejecting a true null is the classic Type I error. In contrast, not rejecting a true null is the correct decision, and not rejecting the null when the alternative is true is a Type II error.

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